Population-level association between disorder phenotype and either alleles directly affecting the disorder (causal association) or marker alleles flanking the disorder locus (linkage disequilibrium) has enjoyed recent recognition for its potential in the analysis of simple and complex genetic disorders. These associations may be particularly important for the analysis of psychiatric disorders, such as schizophrenia, which have complex etiology and have resisted standard pedigree-based methods. For simple disorders, linkage disequilibrium has been used to refine disease gene location after the gene has been crudely localized using standard methods. But the utility of causal association and linkage disequilibrium for the genetic analysis of complex disorders will depend upon the level of complexity and, for linkage disequilibrium, the evolutionary history of the population and genes involved. All of these factors are largely unknown. Empirical results, however, suggest the association analyses can in some instances be very effective at pinpointing loci affecting phenotypic expression. Analytic methods for genetic association data are immature. This project will develop and refine statistical methods to analyze these data, thereby helping to pinpoint genes involved in the etiology of complex disorders. We plan to apply these methods to data on three psychiatric disorders, namely schizophrenia, attention deficit/ hyperactivity disorder, and Alzheimer's disease, as well as to data on simple genetic disorders.